Effects of media reporting on mitigating spread of COVID-19 in the early phase of the outbreak

Weike Zhou; Aili Wang; Fan Xia; Yanni Xiao; Sanyi Tang; Weike Zhou; Aili Wang; Fan Xia; Yanni Xiao; Sanyi Tang

doi:10.3934/mbe.2020147

Mathematical Biosciences and Engineering

2020, Volume 17, Issue 3: 2693-2707. doi: 10.3934/mbe.2020147

Previous Article Next Article

Research article Special Issues

Effects of media reporting on mitigating spread of COVID-19 in the early phase of the outbreak

1.
College of Mathematics and Information Science, Shaanxi Normal University, Xi’an 710062, China
2.
School of Mathematics and Information Science, Baoji University of Arts and Sciences, Baoji 721013, China
3.
School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, China

Received: 11 February 2020 Accepted: 06 March 2020 Published: 10 March 2020

The 2019 novel coronavirus disease (COVID-19) is running rampantly in China and is swiftly spreading to other countries in the world, which causes a great concern on the global public health. The absence of specific therapeutic treatment or effective vaccine against COVID-19 call for other avenues of the prevention and control measures. Media reporting is thought to be effective to curb the spreading of an emergency disease in the early stage. Cross-correlation analysis based on our collected data demonstrated a strong correlation between media data and the infection case data. Thus we proposed a deterministic dynamical model to examine the interaction of the disease progression and the media reports and to investigate the effectiveness of media reporting on mitigating the spread of COVID-19. The basic reproduction number was estimated as 5.3167 through parameterization of the model with the number of cumulative confirmed cases, the number of cumulative deaths and the daily number of media items. Sensitivity analysis suggested that, during the early phase of the COVID-19 outbreak, enhancing the response rate of the media reporting to the severity of COVID-19, and enhancing the response rate of the public awareness to the media reports, both can bring forward the peak time and reduce the peak size of the infection significantly. These findings suggested that besides improving the medical levels, media coverage can be considered as an effective way to mitigate the disease spreading during the initial stage of an outbreak.
- COVID-19,
- media reporting,
- mathematical model,
- basic reproduction number,
- sensitivity analysis
Citation: Weike Zhou, Aili Wang, Fan Xia, Yanni Xiao, Sanyi Tang. Effects of media reporting on mitigating spread of COVID-19 in the early phase of the outbreak[J]. Mathematical Biosciences and Engineering, 2020, 17(3): 2693-2707. doi: 10.3934/mbe.2020147

Related Papers:

Abstract

The 2019 novel coronavirus disease (COVID-19) is running rampantly in China and is swiftly spreading to other countries in the world, which causes a great concern on the global public health. The absence of specific therapeutic treatment or effective vaccine against COVID-19 call for other avenues of the prevention and control measures. Media reporting is thought to be effective to curb the spreading of an emergency disease in the early stage. Cross-correlation analysis based on our collected data demonstrated a strong correlation between media data and the infection case data. Thus we proposed a deterministic dynamical model to examine the interaction of the disease progression and the media reports and to investigate the effectiveness of media reporting on mitigating the spread of COVID-19. The basic reproduction number was estimated as 5.3167 through parameterization of the model with the number of cumulative confirmed cases, the number of cumulative deaths and the daily number of media items. Sensitivity analysis suggested that, during the early phase of the COVID-19 outbreak, enhancing the response rate of the media reporting to the severity of COVID-19, and enhancing the response rate of the public awareness to the media reports, both can bring forward the peak time and reduce the peak size of the infection significantly. These findings suggested that besides improving the medical levels, media coverage can be considered as an effective way to mitigate the disease spreading during the initial stage of an outbreak.

References

[1]	Wuhan Municipal Health Commission, available from: http://wjw.wuhan.gov.cn/front/web/showDetail/2020010309017 (accessed on 8 February 2020).
[2]	World Health Organization, available from: https://www.who.int/health-topics/coronavirus (accessed on 8 February 2020).
[3]	P. Zhou, X. Yang, X. Wang, B. Hu, L. Zhang, W. Zhang, et al., Discovery of a novel coronavirus associated with the recent pneumonia outbreak in humans and its potential bat origin, BioRxiv, (2020). doi: 10.1101/2020.01.22.914952.
[4]	C. Huang, Y. Wang, X. Li, L. Ren, J. Zhao, Y. Hu, et al., Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China, Lancet, 395 (2020), 497-506.
[5]	National Health Commission of the People's Republic of China, available from: http://www.nhc.gov.cn/xcs/yqtb/202002/6c305f6d70f545d59548ba17d79b8229.shtml (accessed on 8 February 2020).
[6]	National Health Commission of the People's Republic of China, available from: http://www.nhc.gov.cn/xcs/zhengcwj/202002/18c1bb43965a4492907957875de02ae7.shtml (accessed on 8 February 2020).
[7]	I. S. Kristiansen, P. A. Halvorsen, D. Gyrd-Hansen, Influenza pandemic: perception of risk and individual precautions in a general population, Cross sectional study, BMC Public Health, 7 (2007), 48.
[8]	U. C. de Silva, J. Warachit, S. Waicharoen, M. Chittaganpitch, A preliminary analysis of the epidemiology of influenza A(H1N1) virus infection in Thailand from early outbreak data, June-July 2009, Euresurveilance, 14 (2009), 1-3.
[9]	D. Roth, B. Henry, Social Distancing as a Pandemic Influenza Prevention Measure, National Collaborating Centre for Infectious Diseases, (2011).
[10]	F. Huang, S. S. Zhou, S. S. Zhang, H. J. Wang, L. H. Tang, Temporal correlation analysis between malaria and meteorological factors in Motuo County, Tibet, Malaria J., 10 (2011), 54.
[11]	G. E. Box, G. M. Jenkins, G. C. Reinsel, Time series analysis: forecasting and control, Forth edition, John Wiley & Sons, 2015.
[12]	Health Commission of Hubei Province, available from: http://wjw.hubei.gov.cn/bmdt/ztzl/fkxxgzbdgrfyyq/ (accessed on 8 February 2020).
[13]	B. Tang, X. Wang, Q. Li, N. L. Bragazzi, S. Tang, Y. Xiao, et al., Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions, J. Clin. Med., 9 (2020), 462.
[14]	Chinese Center for Disease Control and Prevention. Report about 2019-nCoV, available from: http://www.chinacdc.cn/yyrdgz/202001/P020200128523354919292.pdf (accessed on 8 February 2020).
[15]	M. W. Shen, Z. H. Peng, Y. N. Xiao, L. Zhang, Modelling the epidemic trend of the 2019 novel coronavirus outbreak in China, BioRxiv, (2020).
[16]	Wuhan Municipal Health Commission, available from: http://wjw.wuhan.gov.cn/front/web/showDetail/2020011109035 (accessed on 8 February 2020).
[17]	J. A. Backer, D. Klinkenberg, J. Wallinga, The incubation period of 2019-nCoV infections among travellers from Wuhan, China, MedRxiv, (2020).
[18]	Q. Li, X. Guan, P. Wu, X. Wang, L. Zhou, Y. Tong, Early transmission dynamics in Wuhan, China, of novel coronavirus infected pneumonia, New Engl. J. Med., (2020).
[19]	S. Zhao, S. Musa, Q. Lin, J. Ran, G. Yang, W. Wang, et al., Estimating the unreported number of novel coronavirus (2019-nCoV) vases in China in the first half of January 2020: a data-driven modelling analysis of the early outbreak, J. Clin. Med., 9 (2020), 388.
[20]	J. Chan, S. Yuan, K. Kok, K. To, H. Chu, J. Yang, et al., A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster, Lancet, 395 (2020), 514-523.
[21]	J. T. Wu, K. Leung, G. M. Leung, Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study, Lancet, 395 (2020), 689-697.
[22]	Y. Liu, A. A. Gayle, A. Wilder-Smith, J. Rocklov, The reproductive number of COVID-19 is higher compared to SARS coronavirus, J. Travel. Med., (2020), 1-4.
[23]	The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team, Vital Surveillances: The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19)-China, 2020, China CDC weekly, 2 (2020), 113-122.
[24]	Wuhan Municipal Health Commission, available from: http://wjw.wuhan.gov.cn/front/web/showDetail/2020012409132 (accessed on 4 March 2020).

Reader Comments

Your name:*

Email:*
© 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)